Probabilistic Skyline Operator over Sliding Windows

Publisher:
Elsevier
Publication Type:
Journal Article
Citation:
Information Systems, 2013, 38 (8), pp. 1212 - 1233
Issue Date:
2013-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2013005440OK.pdf1.19 MB
Adobe PDF
Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of efficiently computing the skyline over sliding windows on uncertain data elements against probability thresholds. Firstly, we characterize the properties of elements to be kept in our computation. Then, we show the size of dynamically maintained candidate set and the size of skyline. Novel, efficient techniques are developed to process continuous probabilistic skyline queries over sliding windows. Finally, we extend our techniques to cover the applications where multiple probability thresholds are given, top-k skyline data objects are retrieved, or elements have individual life-spans. Our extensive experiments demonstrate that the proposed techniques are very efficient and can handle a high-speed data stream in real time.
Please use this identifier to cite or link to this item: